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Graphics and statistics for cardiology: clinical prediction rules

Graphs and tables are indispensable aids to quantitative research. When developing a clinical prediction rule that is based on a cardiovascular risk score, there are many visual displays that can assist in developing the underlying statistical model, testing the assumptions made in this model, evalu...

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Detalles Bibliográficos
Autores principales: Woodward, Mark, Tunstall-Pedoe, Hugh, Peters, Sanne AE
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5529956/
https://www.ncbi.nlm.nih.gov/pubmed/28179372
http://dx.doi.org/10.1136/heartjnl-2016-310210
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author Woodward, Mark
Tunstall-Pedoe, Hugh
Peters, Sanne AE
author_facet Woodward, Mark
Tunstall-Pedoe, Hugh
Peters, Sanne AE
author_sort Woodward, Mark
collection PubMed
description Graphs and tables are indispensable aids to quantitative research. When developing a clinical prediction rule that is based on a cardiovascular risk score, there are many visual displays that can assist in developing the underlying statistical model, testing the assumptions made in this model, evaluating and presenting the resultant score. All too often, researchers in this field follow formulaic recipes without exploring the issues of model selection and data presentation in a meaningful and thoughtful way. Some ideas on how to use visual displays to make wise decisions and present results that will both inform and attract the reader are given. Ideas are developed, and results tested, using subsets of the data that were used to develop the ASSIGN cardiovascular risk score, as used in Scotland.
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spelling pubmed-55299562017-07-31 Graphics and statistics for cardiology: clinical prediction rules Woodward, Mark Tunstall-Pedoe, Hugh Peters, Sanne AE Heart Review Graphs and tables are indispensable aids to quantitative research. When developing a clinical prediction rule that is based on a cardiovascular risk score, there are many visual displays that can assist in developing the underlying statistical model, testing the assumptions made in this model, evaluating and presenting the resultant score. All too often, researchers in this field follow formulaic recipes without exploring the issues of model selection and data presentation in a meaningful and thoughtful way. Some ideas on how to use visual displays to make wise decisions and present results that will both inform and attract the reader are given. Ideas are developed, and results tested, using subsets of the data that were used to develop the ASSIGN cardiovascular risk score, as used in Scotland. BMJ Publishing Group 2017-04 2017-02-08 /pmc/articles/PMC5529956/ /pubmed/28179372 http://dx.doi.org/10.1136/heartjnl-2016-310210 Text en Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/ This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
spellingShingle Review
Woodward, Mark
Tunstall-Pedoe, Hugh
Peters, Sanne AE
Graphics and statistics for cardiology: clinical prediction rules
title Graphics and statistics for cardiology: clinical prediction rules
title_full Graphics and statistics for cardiology: clinical prediction rules
title_fullStr Graphics and statistics for cardiology: clinical prediction rules
title_full_unstemmed Graphics and statistics for cardiology: clinical prediction rules
title_short Graphics and statistics for cardiology: clinical prediction rules
title_sort graphics and statistics for cardiology: clinical prediction rules
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5529956/
https://www.ncbi.nlm.nih.gov/pubmed/28179372
http://dx.doi.org/10.1136/heartjnl-2016-310210
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